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Renewable Portfolio Standards (RPS) and carbon emission trading (CET) system are the top-level system design of China's energy low-carbon transformation, which have great strategic significance for realizing the "carbon peak in 2030 and carbon neutrality in 2060". At present, China's tradable green certificates market and CET market are still in the initial stage. The implementation single system may have diverse trials and errors in its initial stage, and the market activity and transaction frequency are low. Therefore, this paper aims to explore whether the synergistic effect between the two systems can effectively promote China's energy low-carbon transformation. This paper establishes the system dynamic model of the synergistic effect between the RPS and CET in China's electricity market to reveal the influence mechanism and the synergistic effect. The results show that: (1) There is a positive synergistic effect between the RPS and CET, which will change with the institutional parameters. (2) The simultaneous implementation of the RPS and CET can effectively stimulate market vitality and promote the development of the renewable energy industry. (3) Higher quota and lower benchmark price can optimize power source structure, and improve social welfare and institutional performance. [ABSTRACT FROM AUTHOR]

Renewable Portfolio Standards (RPS) is a mandatory institutional change to promote low-carbon energy transformation and renewable energy development. Its successful implementation requires the scientific design of relevant incentive mechanisms and rules. To make up for the defects in the current RPS mechanism design and the problems exposed in the Tradable Green Certificate (TGC) market, this paper takes China as an example and uses the system dynamics method to study the supply side incentives. The results show that: (1) Scientific setting the relevant system parameters of RPS (such as quota, benchmark price and penalty) and promoting the electricity market reform will effectively stimulate the power generation and investment on the supply side, and improve manufacturers' profit. (2) Higher quotas and lower benchmark prices can increase the manufacturers' power generation, profit and investment, and stimulate the supply side to conduct TGC transactions. However, when the penalty is set at different multiples of the benchmark price, the incentive effect on supply side power generation, investment and profit differ. (3) Marketed on-grid prices can significantly stimulate the supply side and promote renewable energy development. This paper can provide reference for the design of RPS incentive mechanism and institutional parameters. [ABSTRACT FROM AUTHOR]

Electricity market-oriented reform and carbon emissions trading, as the main policies implemented in China's power sector, have a profound impact on China's green and low-carbon transition by promoting resource allocation efficiency and internalizing external environmental costs, respectively. Therefore, this paper constructed a dynamic recursive CGE model to measure the energy, economic, and environmental impacts of carbon emissions trading and electricity market-oriented reform from electricity market structure and pricing mechanism. The results show that the two policies have a synergistic effect on industrial structure optimization, energy consumption structure optimization, and carbon emission reduction. Specifically, the share of value-added of the tertiary sector, the growth rate of coal consumption, the share of thermal power consumption, and carbon emissions in 2030 are reduced by 5.70 %, 18.29 %, 2.55 %, and 2.838 trillion tons, respectively, compared with the scenario without carbon emissions trading and electricity market-oriented reform. However, imperfectly competitive market structures outperform perfectly competitive market structures in energy consumption structure and carbon emission reduction. Electricity price regulation is also more beneficial to GDP growth and increase in residential disposable income compared to price liberalization. To this end, returning emission trading scheme revenues to residents can effectively mitigate the adverse impacts caused by market-oriented reforms. • EMR is involved in market structure, pricing mechanisms, and market regulation. • EMR and CET have a synergistic effect on carbon reduction. • Energy consumption structure is better in imperfectly competitive market. • Electricity price regulation is more beneficial to GDP growth. • Returning ETS revenue to residents increases per capita disposable income. [ABSTRACT FROM AUTHOR]

China's electricity market reform poses an urgent demand for grid parity of renewable energy (RE), however, the high initial investment cost makes it difficult to achieve. Although feed-in tariff (FIT) and renewable portfolio standards (RPS) schemes are both practical policy tools to support the development of the RE industry, which policy is more consistent with the goal of grid parity? Accordingly, based on the system dynamic model, this research studies the levelized cost of RE (LCOE) under FIT and RPS, respectively. The results show that: First, under the current FIT scheme, wind (onshore) and photovoltaic (PV) power both cannot achieve grid parity. To realize it, extra payouts in four categories of areas should at least be 0.236, 0.244, 0.299 and 0.261 CNY/kWh. Similarly, additional subsidies for PV in Tibet and the northwest region except Tibet need to be 0.924 and 0.764 CNY/kWh. Second, under the RPS, wind (onshore) power can basically achieve grid parity, but PV cannot. Subsidies for PV need at least to be 0.525 and 0.364 CNY/kWh to achieve grid parity. Therefore, compared with the current FIT in China, the policy combination of FIT and RPS adjusted to local conditions is more conducive to realizing grid parity. • Under the current feed-in tariff (FIT), wind and photovoltaic (PV) cannot achieve grid parity. • Under the renewable portfolio standards (RPS), wind can achieve grid parity, but PV cannot. • The policy mix of FIT and RPS adjusted to local conditions can realize grid parity. [ABSTRACT FROM AUTHOR]

With the economic transformation and regional economic restructuring of China, there is a significant inter-regional transfer trend of industries among the eastern, central, western and northeastern regions. The industrial transfer is able to change the spatial distribution of regional energy intensity by affecting the regional industrial structure, thus impacting the convergence of energy intensity. This paper established a spatial Durbin panel model, and used the relevant data of thirty administrative regions of China from 2004 to 2017 to empirically study the impacts of industrial transfer on regional energy intensity. The results showed that: (1) As a whole, the energy intensity of China's regions was low in the southeast region and high in the northwest region, and there was a significant positive spatial autocorrelation among the energy intensity of different regions. (2) There was β -convergence in the regional energy intensity. It indicated that, on the one hand, the differences in the energy intensity of China's different regions were being gradually narrowed; on the other hand, the energy intensity of each region would converge to its own steady state. (3) The industrial transfer and economic development could promote the convergence of the regional energy intensity. • China's economic transition and regional economic restructuring promoted industrial transfer. • The regional energy intensity showed a decreasing trend from northwest to southeast. • Industrial transfer could promote the convergence of energy intensity. • A spatial Durbin panel model was used to prove the regional energy intensity convergence of China. [ABSTRACT FROM AUTHOR]

As subsidies continue to fall, the technology and cost performance of distributed photovoltaic (PV) determines the progress of its grid parity. Based on the discussion of technology and cost, this paper analyzed the economic performance of China's distributed PV industry by utilizing the two indicators of levelized cost of energy (LCOE) and internal rate of return (IRR). The results show that: firstly, the current external environment is generally conducive to the development of distributed PV, but there are still some constraints. Secondly, with the decrease of unit investment cost, distributed PV can achieve the goal of parity before 2025. Thirdly, distributed PV projects in the three types of solar energy resources all have high IRR, and the economic performance is better for the projects with high proportion of spontaneous self-use. At the end of the paper, policy recommendations are offered as references for the government. • We comprehensively analyzed the technology and cost performance of China's distributed PV. • We focused on the trend and decline path of China's distributed PV costs. • The LCOE of distributed PV in China is expected to achieve full parity in 2025. • Except 100% grid-connected mode, the IRR of distributed PV power plants in three areas is higher than 8% which has shown good economic benefits. [ABSTRACT FROM AUTHOR]

Abstract Promoting wind power is a long-term strategy of China to respond to both energy shortage and environmental pollution. Stimulated by various incentive policies, wind power generation in China has achieved tremendous growth. However, the China's wind power industry is still in its early development stage and various problems have emerged, seriously challenging the healthy functioning of the industry. Based on micro-data on wind power listed companies, the four-stage Data Envelopment Analysis (DEA) model is used to measure the technical efficiency of China's wind power enterprises and sketch the development of the wind power industry at the micro level. The results show that there exist non-efficiency problems arising from the diseconomies of scale in China's wind power industry during 2011–2015. The average value of the efficiency of wind power enterprises is 32.5%. According to the subsample analysis, large-scale enterprises, private-owned enterprises and enterprises taking wind farm conduction and operation as their main business, as well as enterprises located in the three northern area, have the highest efficiency in their respective categories. Drawn on this analysis, conclusions and policy implications are provided at the end of the paper. Highlights • Reviewed literature on the efficiency of China's wind power industry systematically. • Used the four-stage DEA method to analyze micro-data on wind power listed companies with the goal of delineating the efficiency of the development of China's wind power industry. • Analyzed wind power enterprises from the following four aspects: the scale of enterprises, their regions, nature, and the upstream and downstream of their industrial chain. • Made policy recommendations for the development of China's wind power industry. [ABSTRACT FROM AUTHOR]

Abstract China is experiencing renewable energy support schemes evolution from feed-in tariff (FIT) to renewable portfolio standards (RPS) scheme, which can be significantly influenced by renewable and conventional electricity producers strategies. This paper applies evolutionary game theory and system dynamics (SD) model to examine electricity producers strategies in this scheme context. We utilize the data from Chinese wind power industry for simulation to represent evolution of strategies, and research impacts of scheme parameters (subsidy, quota, and fine) on electricity producers and tradable green certificate (TGC) market operation. The results show that, to ensure all the electricity producers willing to trade TGC, scheme parameters should be within a reasonable range. Moreover, the stage descent mode of subsidy and higher level of fine will help the electricity producers accept the RPS scheme as soon as possible and promote the scale of TGC transaction, but the quota requirement should be avoided too low. At the end of the paper, policy implications are offered as references for the government. [ABSTRACT FROM AUTHOR]

Abstract The imbalance and insufficiency of China's regional economic development has led to huge differences in regional energy efficiency. Reducing the differences in regional energy efficiency has become an urgent energy issue in China. The constant absorption of foreign direct investment (FDI) has brought advanced technologies to China, which has an important impact on China's energy efficiency. To explore whether FDI can reduce regional energy efficiency differences, this paper investigates the existence of energy intensity convergence while incorporating foreign direct investment (FDI). Since existing research on regional energy intensity convergence lacks of consideration of the data spatial dependence, we focus on spatial econometric model to test energy intensity convergence. We use panel data of 30 provinces in China over the period of 2005–2014 to test energy intensity convergence by β convergence model. The empirical results show that considering the spatial dependence of the data, FDI can promote the formation of conditional energy intensity convergence. Further analysis found that the spillover effect of FDI plays an important role in this formation. In addition, the convergence speed accelerates after considering the spatial dependence. Finally, the spillover effect of FDI, which is global, inhibits the declining speed of energy intensity during the research period. The scale effect of FDI and energy rebound effect plays an important role in the effect of FDI on energy intensity. These results show that guiding foreign investment more reasonably in each province in China can make contributions to the reduction of energy efficiency differences. Highlights • Use spatial econometric approach to test the convergence of energy intensity. • FDI can promote the convergence of energy intensity. • The spillover effect of FDI plays an important role in the formation of energy intensity convergence. • The effect of FDI on energy intensity has brought a rebound effect. [ABSTRACT FROM AUTHOR]

Abstract Studying the economic performance is of great significance to the policy improvement and investment decisions making of concentrated solar power (CSP) industry. This study developed a cost-benefit model to analyze the economic benefits of CSP industry, under the current technological level and policy system of China. The results showed that: Firstly, the huge initial costs resulted in that the investment of CSP industry had to bear a long capital recovery period, which might add the investment risks; meanwhile it was still economically feasible because of better expected benefits. Secondly, for CSP industry, the internal rate of return mainly varied from 8% to 12%, and the average levelized cost of energy was $0.148/kWh; the economic performance of CSP industry was attractive from the multiple dimensions analysis, and the benchmark feed-in-tariffs could provide effective support for the CSP industry development of China. Thirdly, adopting solar tower CSP technology was better choice to improve the economic benefits of CSP industry, compared with parabolic trough and linear Fresnel CSP technologies. Lastly, the direct normal irradiation, initial costs, annual electricity production and loans ratio had important impacts on the economic benefits of CSP industry, and should be paid more attention in investment decisions. Graphical abstract The policy system determines the costs and benefits of CSP industry by the economic parameters, and then affects the economic performance of CSP industry. The analysis on the economic benefits can provide scientific basis references for the industrial policy improvement and investment decisions. Image Highlights • Develop a cost-benefit model to analyze the economic performance of CSP industry. • Capital recovery period, usually more than 11 years, adds investment risks of CSP. • In spite of high initial costs, investment in CSP industry is economically feasible. • IRR of CSP industry mainly varied from 8% to 12%, with average LCOE of $0.148/kWh. [ABSTRACT FROM AUTHOR]

The prospective cost-benefit of CSP (concentrated solar power) is the attention focus for policy-making and investment decisions. In order to analyze cost-benefit evolution of CSP, the paper adopted the net present value and discounted cash flows techniques to develop a mathematical model, and calculated LCOE (levelized cost of energy) of CSP between 2018 and 2050 by taking the CSP industry of China as an example. The results show that: Firstly, CSP has a large potential in the LCOE reduction, and the values of parabolic trough and solar tower CSP systems reduce by 46%–57% and 47%–56% from 2018 to 2050, respectively. Secondly, predicted evolution for the LCOE of CSP strongly depends, not only on the cumulative installed capacity determined by the specific growth paths of Blue Map and Roadmap Scenarios, but also on the learning curves impacted by technical progress and experience accumulation. Thirdly, to select the sites with higher direct normal irradiation and land cost exemption is crucial to improve cost-benefit evolution of CSP. Lastly, the expected returns (i.e. discount rate) have important effect on the LCOE evolution of CSP, high expected returns lead to high the LCOE, and vice versa. [ABSTRACT FROM AUTHOR]

In order to find out the driving factors that affect the performance of PV industry in China, this article analyzes the panel data of 17 photovoltaic cells enterprise from 2008 to 2014. The total factor productivity growth is decomposed to test the performance of the photovoltaic industry and the level of technological progress. The empirical results show that the growth in output of Chinese PV industry mainly relies on technological progress, while the relative frontier technology efficiency does not change with time, and the allocation efficiency and scale economy function contributes little to the change of total factor productivity. Analysis shows that the way to obtain the future development of China PV industry is to rely on technological progress and market competition mechanism. [ABSTRACT FROM AUTHOR]

Among the regulatory policies, feed-in tariffs (FIT) and renewable portfolio standards (RPS) are the most popular to promote the development of renewable energy power industry. This paper uses system dynamics (SD) to establish models of long-term development of the renewable energy power industry under FIT and RPS schemes, and provides a case study of China's wind power industry by using scenario analysis method. The model, on the one hand, not only clearly shows the complex logical relationship between the factors but also reveals the process of coordination between the two policy tools in the development of the renewable energy power industry. On the other hand, it provides a reference for scholars to study similar problems in different countries, thereby facilitating an understanding of the renewable energy power's long-term sustainable development pattern under FIT and RPS schemes, and helping to provide references for policy-making institutions. The results show that the integrate implementation of FIT and RPS can promote long-term and rapid development of China's wind power industry given the constraints and actions of the mechanisms of RPS quota proportion, the tradable green certificates (TGC) valid period, and fines. In addition, in the period of the construction of the TGC market, RPS quota growth rate and fine have a no significant effect on industrial development, however, with TGC market game becoming more and more fierce, both of them have a significant positive impact on the long-term development of the industry. TGC valid period has little effect on industrial development in our study. At the end of the paper, policy implications are offered as references for the government. [ABSTRACT FROM AUTHOR]

Among the regulatory policies, feed-in tariffs (FIT) and renewable portfolio standards (RPS) are the most popular to promote the development of renewable energy power industry. This paper uses system dynamics (SD) to establish models of long-term development of China's biomass power industry under FIT and RPS schemes, and provides a case study by using scenario analysis method. The model, on the one hand, not only clearly shows the complex logical relationship between the factors but also reveals the process of coordination between the two policy tools in the development of the industry. On the other hand, it provides a reference for scholars to study similar problems in different countries, thereby facilitating an understanding of biomass power's long-term sustainable development pattern under FIT and RPS schemes, and helping to provide references for policy-making institutions. The results show that in the perfect competitive market, the implementation of RPS can promote long-term and rapid development of China's biomass power industry given the constraints and actions of the mechanisms of RPS quota proportion, the TGC valid period, and fines, compared with FIT. At the end of the paper, policy implications are offered as references for the government. [ABSTRACT FROM AUTHOR]

Among the regulatory policies, feed-in tariffs (FIT) and renewable portfolio standards (RPS) are the most popular to promote the development of renewable energy power industry. They can significantly contribute to the expansion of domestic industrial activities in terms of sustainable energy. This paper uses system dynamics (SD) to establish models of long-term development of China’s waste incineration power industry under FIT and RPS schemes, and provides a case study by using scenario analysis method. The model, on the one hand, not only clearly shows the complex logical relationship between the factors but also assesses policy effects of the two policy tools in the development of the industry. On the other hand, it provides a reference for scholars to study similar problems in different countries, thereby facilitating an understanding of waste incineration power’s long-term sustainable development pattern under FIT and RPS schemes, and helping to provide references for policy-making institutions. The results show that in the perfect competitive market, the implementation of RPS can promote long-term and rapid development of China’s waste incineration power industry given the constraints and actions of the mechanisms of RPS quota proportion, the TGC valid period, and fines, compared with FIT. At the end of the paper, policy implications are offered as references for the government. [ABSTRACT FROM AUTHOR]

As the primary source sector of carbon emissions, the power industry's green innovation is an indispensable component of China's low-carbon transformation. This paper took China's Carbon Emission Trading Scheme as a quasi-natural experience and adopted the synthetic control method to evaluate the impact of Carbon Emission Trading Scheme pilot policy on power industry's green innovation based on the provincial industrial level data. Furthermore, this paper examined the impact mechanisms of Carbon Emission Trading Scheme on the power industry's green innovation through policy comparison, moderating and mediating effect analyses. The research findings show that: 1) there is heterogeneity in Carbon Emission Trading Scheme's effectiveness in inducing green innovation in China, the power industry only in Beijing and Guangdong has been significantly promoted, while other pilots have not; 2) the success of Beijing and Guangdong can be attributed to distinctive features of their carbon market and power industry, including the refined quota accounting mechanism, the application of paid quota allocation, the larger enterprise scale and more research and development investment; 3) enterprise scale and research and development investment have positive moderating effect and mediating effect in the promotional effect of the Carbon Emission Trading Scheme on green innovation respectively. Finally, some policy recommendations are put forward to promote the power industry's green innovation and carbon market construction. • Evaluate the impact of China's CETS on the power industry's green innovation in each pilot. • The CETS effects among pilots are heterogeneous, only significant in Beijing and Guangdong. • Rational CETS mechanism design could improve the power industry's green innovation. • Enterprise scale and R&D investment positively moderate and mediate the CETS effect. [ABSTRACT FROM AUTHOR]

With the support of incentive policies, the diffusion of wind power has achieved tremendous achievements in China. However, behind this rapid expansion, it is raised a question: what are the driving forces behind the diffusion of wind power? And which policies are more efficient to improve the diffusion rate of wind power? To scientifically answer this question, this paper combines system dynamics and the two-factor learning curve to investigate the dynamic diffusion process of wind power. The results show that: (1) The demand-pull policy through feed-in tariff (FIT) policy can promote the diffusion of wind power; (2) The technology-push policy through R&D policy also promotes the diffusion of wind power; (3) A higher level of FIT is more efficient to expand the installed capacity of wind power, in addition, a higher level of R&D intensity is more efficient for cost reduction; (4) The coefficient of learning by doing of wind power is 0.0274 and the coefficient of learning by research of wind power is 0.2540, which indicates China's wind power industry is transitioning from price subsidies to technology innovation policies. The research results can enrich the research on the diffusion of wind power and provide a reference for other regions to study the diffusion of renewable energy. • Both demand-pull and technology-push can promote the diffusion of wind power. • The coefficient of learning-by-doing and learning-by-researching is 0.0274, 0.2540 • The reduction in wind power costs is driven more by innovation policies. • A higher level of FIT policy is more efficient to expand the installed capacity. • A higher level of R&D intensity is more efficient for cost reduction. [ABSTRACT FROM AUTHOR]

With the upgrading of urbanization and improvement of living standards, the volume of municipal solid waste (MSW) is increasing in China. The waste-to-energy (WTE) incineration industry promotes the harmless disposal and recycling of MSW. It is an important part of the energy conservation and emission reduction tasks of “12th Five-Year Plan” period (2011–2015). Based on the development status of WTE plants in China, this paper makes an analysis of the WTE incineration industry from two aspects. The one is the analysis of political, economic, social and technological factors that influence the external environment of this industry. The other one is the discussion of technologies, costs and performances of some WTE plants in China, including a detailed cost-benefit analysis. It proves that the external environment is conducive to the development of WTE incineration industry and this industry is faced with good market prospects. Also, the net profit margin and return on investment (ROI) of WTE plants is attractive, up to 25% and 18% respectively. The pay back period is 12.73 years and the internal rate of return (IRR) is 10.94%. Thus, WTE plant has good profitability and economic benefit. Besides, WTE incineration has significant environmental benefits. [ABSTRACT FROM AUTHOR]

The oil crisis and the successful commercial exploitation of shale gas in America have made shale gas become the focus of global energy industry. Shale gas industry will be developed mainly in the future. Sichuan has natural geographical advantages and becomes the main battlefield of shale gas in China. So it is necessary and urgent to analyze the current situation of Sichuan shale gas. This paper introduces the status quo of shale gas in Sichuan, and systematically analyzes the industrial environment for developing Sichuan shale gas from four aspects of policy, economy, society, technology. Then the issues facing Sichuan are discussed. Finally, the paper puts forward some corresponding recommendations to provide certain references to the development of shale gas industry in Sichuan. [ABSTRACT FROM AUTHOR]

To adjust the energy structure, protect the environment and deal with climate change, China has proposed that non-fossil energy would constitute 15 percent of the total energy consumption at the end of the “13th Five-Year Plan” period (2016–2020), and the use of biomass would account for 4 percent of primary energy consumption. Firstly, the current situation, the internal environment and the external environment of the biomass direct combustion power generation are analyzed. Then, the financial model of biomass direct combustion power generation project is established, and contrasts with other major new energy projects are carried out in terms of operation models, opportunities and risks so as to explore the investment features of this project in depth. Finally, appropriate investment strategies are proposed with respect of the investors, and policy recommendations for the development of the industry are attempted as well. [ABSTRACT FROM AUTHOR]

Abstract: Compared to the Feed-in tariff in China, the Renewable Portfolio Standard (RPS) could not only help to change the driving force of renewable energy industry development, but also provide the renewable energy industry with incentives to achieve the governments' planned goal. This paper first compares the features of RPS of the major industrialized countries. Second the barriers of implementing the Renewable Portfolio Standard in China are analyzed from five aspects. Finally, based on the above analysis, this paper puts forward relative institutional arrangements for the implementation of Renewable Portfolio Standard in China making recommendations for the development of renewable energy industry. [Copyright &y& Elsevier]

Renewable portfolio standards are essential means to promote the transition to low-carbon energy by encouraging obligated subjects to purchase tradable green certificates. However, the trade-off between Renewable portfolio standards' cost and effectiveness is a challenge for the government, because they want to support the development of renewable energy at the lowest cost. This paper constructs a coevolution model for a renewable energy system incorporating Renewable portfolio standards to explore how incentive mechanisms impact the cost and effectiveness of Renewable portfolio standards. The simulation results show that with the coevolution of the RE system, Renewable portfolio standards' effectiveness gradually rises; concurrently, its cost increases first before later decreasing. However, the path-dependence of the behavioural evolution of the tradable green certificate market players hinders further improvements in Renewable portfolio standards' cost-effectiveness. In addition, high quotas and price collars close to TGC value improve the cost-effectiveness, whilst the sloped penalty mechanisms, banking mechanisms with a valid period longer than one year, and borrowing mechanisms significantly reduce costs. On this basis, the government can design dynamic incentive mechanisms to guide the market players' behavioural evolution and decrease costs whilst also ensuring effectiveness. • The effectiveness of Renewable portfolio standards (RPS)gradually rises. • The cost of RPS first increases and then decreases. • Higher quota and price collars close to value improve the cost-effectiveness of RPS. • Penalty, banking and borrowing mechanisms can reduce the cost of RPS. [ABSTRACT FROM AUTHOR]

Under the downward pressure of the economy, China's extensive economic growth that relies on factor input is difficult to sustain. Scientific analysis of the industrial restructuring and energy consumption has become the key to realizing China's economic growth from high-speed to high-quality. Based on the fully-modified least square method and panel vector error correction model, this paper explores the equilibrium relationship and Granger causality among the industrial restructuring, energy consumption and economic growth at aggregated and disaggregated levels. The results show that: (1) The effect of industrial structure rationalization on economic growth is higher than that of industrial structure upgrading. When emphasizing industrial structure upgrade, the more reliable industrial policy to achieve China's sustainable economic growth is to pay attention to the industrial structure rationalization, especially in western China. (2) The impacts of natural gas and renewable energy consumption on economic growth are much smaller than coal and electricity consumption; more energy policies should be designed to encourage clean energy development. • The industrial structure rationalization has highest contribution to the economic growth of eastern China, followed by central and western China. • There exists unidirectional causality from industrial structure upgrading to structure rationalizing in western China and bidirectional causality between them in central China. • Effects of natural gas and renewable energy consumption on economic growth are much smaller than coal and electricity consumption. • Unidirectional long-term causality from renewable energy to economic growth exist in each sub-region. [ABSTRACT FROM AUTHOR]

Abstract: Facing the energy crisis and the requirement of green power, China is making great efforts to fulfill the international cooperation on renewable energy electricity aimed at protecting the security of electricity supply and economy development. This paper firstly utilizes the tool of SWOT strategy analysis to make a research on internal and external environment of international cooperation on renewable energy electricity in China. Secondly discusses the current situation and existing problems of international cooperation from four dimensions of strength, weakness, opportunity and threat. Then, gives a propose of four different kinds of international cooperation strategies based on the combination analysis of SWOT matrix. Finally puts forward the detailed implementation strategies of the policy recommendations for international cooperation on renewable energy electricity. [Copyright &y& Elsevier]

Renewable Portfolio Standards (RPS), as the strategic requirement effectively fits the top-level institution design of China's low-carbon energy transition, will help to promote China's energy structure optimization and power market reform. The success of its implementation depends on the scientific quasi-parameters design of the system. At present, China's tradeable green certificate (TGC) market is still in the voluntary trading stage. There are differences in natural attributes and transaction prices, resulting in the market segmentation and market distortion of the TGC market. Considering the non-neutral technology, this paper uses system dynamics to construct a long-term trading model under China's RPS, and analyzes the impact of relevant system quasi-parameters on the market trading process. The results show that:(1) The scientific quasi-parameters design of the RPS, such as technical conversion coefficient, TGC valid period, TGC benchmark price and RPS quota, will encourage and guide manufacturers to conduct TGC transactions, which will promote the development of renewable energy. (2) The introduction of the technical conversion coefficient can effectively promote TGC transactions, improve China's social welfare and optimize the power source structure. Therefore, the scientific design of the relevant quasi-parameters and strengthening of the supervision mechanism are conducive to implementing the RPS effectively in China. • The case of non-neutral technology is considered in this paper. • Use system dynamics to construct the model considering the non-neutral technology. • Analyze the impact of RPS quasi-parameters on the market trading process. • The scientific parameters can encourage and guide plants to conduct TGC transaction. [ABSTRACT FROM AUTHOR]

Government policies and investments in the photovoltaic power generation industry have contributed to the fast development of the photovoltaic power generation industry through technology push. But how does the research and development (R&D) investment affect the photovoltaic power generation industry, and what is its effect? This is a problem worthy of discussion. In order to answer this question scientifically, this paper constructs a system dynamics model to study the impact of R&D investment on China's photovoltaic power generation industry and analyzes the impact of other incentive policies such as Feed-in Tariff (FIT) on the photovoltaic industry. The results show that: firstly, R&D investment and FIT are conducive to the technological innovation of China's photovoltaic power generation industry. Secondly, a higher level of R&D investment can induce more cost reduction of photovoltaic power industry. Finally, the effect of FIT in promoting the growth of installed capacity of the photovoltaic power generation industry is more obvious. • The relationship between PV industry and technology innovation is reviewed. • R&D investment and FIT are conducive to the technology innovation of PV industry. • A higher level of R&D investment can induce more cost reduction of PV industry. • FIT policy is more effective for the expansion of PV installed capacity. [ABSTRACT FROM AUTHOR]

With the decline in the intensity of subsidy policies, technological progress has become a critical factor in promoting the renewable energy industry's sustainable development. This paper estimates the direction and extent of biased technological progress in China's renewable energy industry from 2009 to 2018. On this basis, by constructing an accounting model for the growth rate of total factor productivity (TFP), this paper empirically analyzes the effects of different factors on TFP growth. The research results indicate that: (1) The TFP of China's renewable energy industry has dropped by 4.60% annually, and the growth of industrial output mainly relied on factor input rather than technological progress. (2) The technological progress and factor allocation of China's renewable energy industry generally show a bias towards the capital. At different stages of the industry's development, it presents different degrees of bias. (3) Technological progress is biased towards capital factor with a lower growth rate of factor efficiency, which hinders the growth of TFP in the renewable energy industry. • This paper reveals the driving mechanism for the development of China's renewable energy industry. • The technological progress and factor allocation of China's renewable energy industry are biased towards the capital. • Capital inefficiency is the fundamental reason for the reduction of TFP in the renewable energy industry. • Improving the level of independent R&D is the key to achieving China's renewable energy industry's sustainable development. [ABSTRACT FROM AUTHOR]

The switch of coal to gas in power generation enterprises is of great significance for tackling air pollution and mitigating climate change. Under China's emissions trading system, power generation enterprises have incentives to switch to low-carbon clean power, and the cost-benefit of switching is the basis of their decision-making. To this end, this paper studied the impact of changes in carbon and fuel prices on switching prices. The results show that: (1) For per yuan increase in the amount of natural gas, coal, and carbon, the switching price increased 4.768, decreased 5.845 and decreased 0.9994 yuan, respectively. (2) The carbon price is relatively low, and the impact of it on switching price is small. (3) The fluctuation in the carbon price, coal price and the natural gas price has a hysteresis effect on switching price. [Display omitted] • This study assesses the coal-to-gas switch possibility in Guangdong Province. • A new mode of operation of coal-to-gas switch is published. • For per yuan increase of carbon price, the switching price decreased 0.99 yuan. • The impact of carbon price fluctuations on switching price has a lag effect. [ABSTRACT FROM AUTHOR]

This paper selected the relevant data of China's thirty administrative regions from 2005 to 2016, and constructed a geographically and temporally weighted regression model of technological progress and energy intensity, to fully analyze the heterogeneous impact of technological progress on energy intensity. The results showed that: (1) The energy intensity of China's different regions, in the long run, had an obvious spatial agglomeration effect and a significant positive correlation in spatial. (2) The spatial heterogeneity of the impact of technological progress on energy intensity changed smoothly and steadily in the temporal dimension, and the dominant factors affecting the energy intensity gradually shifted from foreign direct investment, opening-up degree, human capital to research and development funds from 2005 to 2016. (3) The temporal heterogeneity of the effect of technological progress on energy intensity varied greatly from different spatial dimensions, specifically, the influence of research and development funds on energy intensity was high in the western regions and low in the eastern regions, but that of the foreign direct investment was the opposite, the spatial distribution of the effects of opening-up degree, human capital on energy intensity was dispersed and had no obvious aggregation phenomenon. • GTWR model between technological progress and energy intensity was constructed. • Energy intensity in China had significant spatial agglomeration effect and spatial positive correlation. • Spatial heterogeneity of the impact of technical progress on energy intensity changed steadily. • Temporal heterogeneity of the impact of technical progress on energy intensity varied greatly. • Since 2010, R&D funds became the most effective factor for the reduction of energy intensity. [ABSTRACT FROM AUTHOR]

Carbon emission trading (CET) is an important mechanism for China to achieve carbon emission reduction targets and sustainable development. The success of its implementation depends on the scientific institutional supply design. At present, China is actively promoting the implementation of electricity marketization reform and Renewable Portfolio Standards (RPS), which would change the institutional environment for manufacturers' decision-making and trading, thus impacting CET. Accordingly, this paper aims to establish an evaluation model using the system dynamics method to simulate and evaluate the impact of RPS on CET under the background of electricity marketization reform by designing and combining different policy scenarios. The results show that: (1) The impact of electricity marketization reform and RPS on carbon trading is mainly reflected in carbon emission rights' demand, trading volume, trading price and power generation of manufacturers. (2) Under the situation of marketed electricity price and the absence of RPS, various indicators of the CET market are superior to other policy combinations. (3) Marketed electricity price can effectively stimulate manufacturers' demand for carbon emission rights, increase trading volume, and have a positive impact on CET. However, the implementation of RPS weakens the demand for emission rights, reduces manufacturers' power generation and profit, and harms CET. • Studied the impact of RPS on CET in the context of electricity marketization reform. • Establish an evaluation model by using the SD method. • Marketed electricity price positively affect CET, while the RPS harms CET. • The policy combination of marketed electricity price without RPS is optimal. [ABSTRACT FROM AUTHOR]

• The bargaining strategy based on fuzzy Bayesian learning is proposed. • The bidding strategies meet the Nash bargaining solution and improve negotiation efficiency. • Alternative bidding strategy and simultaneous bidding strategy are compared. • The bidding strategies of bargaining consider information interaction. Bilateral electricity trading is a general transaction mode in electricity market, market subjects' trading strategies will influence social welfare of the market. This study aims to explore effective bargaining strategies promoting the realization of Nash bargaining solution in bilateral electricity trading. The non cooperative bargaining models with preferences in incomplete information and the fuzzy Bayesian learning are combined to optimize the trading strategies. The results show that: (1) the bargaining strategy considering the preferences of both parties to balance the utility maximization and the acceptance of offers is equal allocation of benefits, and it promotes the formation of equilibrium close to social welfare maximization; (2) fuzzy Bayesian learning can accelerate the bargaining process; (3) compared with simultaneous offers bargaining, in alternating offers bargaining, the convergence to equilibrium is faster and parties have first-mover advantage. [ABSTRACT FROM AUTHOR]

China has announced that the mandatory green certificate trading would be implemented in 2021. The mandatory green certificate trading not only fosters the liquidity of the green certificate market but also induces the possibility of market participants taking strategic behavior to gain more market returns. Generally, the self-interested strategic behavior was not conducive to improving market efficiency, thereby impeding the implementation of mandatory green certificate trading. To evaluate the influence of market participants' strategic behavior on the green certificate trading, we embed the strategic behavior model into the artificial green certificate market to simulate the market participants' strategic behavior in green certificate trading. The results indicate: (1) in green certificate market, the strength of the herd effect determines the average compliance costs level; (2) the value-trading strategy is the optimal strategy for renewable obligation subjects to reduce the compliance costs of mandatory green certificate trading; (3) market participants' strategic behavior mainly affect the stability of green certificate price, and the greater the price fluctuation, the slower convergence speed to the equilibrium price. • A strategic behavior model is embedded into artificial green certificate market. • Herd effect of among the market participants is studied. • The influence of market participants' strategic behavior on green certificate trading is analyzed. [ABSTRACT FROM AUTHOR]

To promote energy production and consumption revolution, China introduced Renewable Portfolio Standards (RPS) in 2018. The investigation on power producers' behaviors and the evaluation of the effectiveness of RPS could lay the foundation for the design of RPS, and scientific institution design is the key to promote the development of renewable energy. In this paper, the evolution process of power producers' behaviors has been simulated based on subjective game model, and the performance of RPS has been evaluated based on power producers' shared mental model. The results show that: 1) After the implementation of RPS, the uncertainties of power producers' behaviors decrease gradually, and the game equilibrium has been established, broken, and then rebuilt. 2) When choosing a certain strategy could obtain higher payoff, power producers tend to choose this strategy more frequently in future games. 3) When the fine is two times the price of Tradable Green Certificate (TGC), it becomes the shared mental among power producers to trade TGCs, and RPS becomes effective. Image 1 • Policy parameters influence power producers' behaviors, and power producers' behaviors influence the performance of RPS. • If obeying the rules defined by RPS becomes the shared mental of all power producers, RPS is considered to be effective. • When choosing a certain strategy can obtain higher payoff, power producers tend to choose this strategy more frequently. • When the fine is two times the price of TGC, RPS is effective. [ABSTRACT FROM AUTHOR]

At present, China's PV industry is experiencing a policy-driven to market-driven transition. Whether the endogenous driving force for China's PV industry output growth has been changed is a question of substantial concern? To scientifically answer the question of the endogenous driving force of the output growth of China's PV industry, we empirically analyse the driving force of China's PV industry output growth by constructing an expanded Cobb-Douglas technology production function. The results demonstrate that the output elasticity of research and development (R&D) is between 0.13 and 0.18, which is higher than the level of 0.1 in traditional Chinese manufacturing. Compared with traditional industries, PV industries are more capable of translating their R&D inputs into output revenue; The contribution rate of R&D input to output growth exceeds physical capital and labour factors, indicating that the endogenous driving force of China's PV industry output growth has changed from factor-driven to technological innovation-driven. • Reviewed literature on the output growth of China's photovoltaic industry systematically. • The output growth of photovoltaic industry is studied from the perspective of technological progress. • The R&D output elasticity of China's photovoltaic power generation industry is around 0.13-0.18 • The driving force of China's PV industry output growth has changed from factor-driven to technological innovation-driven. [ABSTRACT FROM AUTHOR]

Energy efficiency improvement is one of the most effective means to achieve energy conservation. The success of energy conservation depends on scientific policy design. So what is the impact of existing policies on energy efficiency? What types of policy tools have the most significant impact on energy efficiency? In response to these problems, this paper took the energy conservation policies promulgated by the Chinese government over the years as samples. This paper used the ridge regression model to analyze policy inducement effect in energy efficiency based on the data envelopment analysis (DEA) model and the policy text evaluation model. The results show that: (1) Energy conservation policies have a positive influence on improving energy efficiency. (2) Among the policy tools, economic incentive tools have the most significant influence on the increase in energy efficiency. Therefore, the government should emphasize the use of economic incentive policy tools and coordinate the relationship between various policy tools to achieve China's stated energy conservation goals. ● This paper makes a quantitative analysis of the energy conservation policy. ● This paper examines the evolution of policy effectiveness. ● This paper analyzes the impact of energy conservation policy on energy efficiency. ● This paper analyzes the impact of policy tools on energy efficiency. [ABSTRACT FROM AUTHOR]

Reasonable design of the tradable green certificate (TGC) system quasi-parameters (benchmark price and technical conversion coefficient) can effectively induce the mutually beneficial cooperation of the TGC market players. However, almost no literature quantitatively estimates the quasi-parameters of TGC system. This paper uses the cooperative game theory to construct the TGC bilateral trade model between renewable energy power generators and distribution power suppliers, and then quantitatively calculates the quasi-parameters of TGC system for social welfare maximization. The results show that: (1) The constructed TGC bilateral trading model guides the mutually beneficial cooperation among market players effectively by realizing benefit expansion and redistribution; (2) The TGC benchmark price and the conversion coefficients can be quantitatively calculated based on the Nash bargaining model. Taking China for example, the benchmark price is 333 yuan/MWh, and the technical conversion coefficients of hydropower, wind power and photovoltaic power are 1, 1.2, and 1.5, respectively. • A tradable green certificate (TGC) bilateral trading model is established. • The benchmark price of TGC in China is 333 yuan/MWh. • The technical conversion coefficients of TGC in China are calculated. • The superiority of Nash bargaining in the quasi-parameters design is validated. [ABSTRACT FROM AUTHOR]

• We consider both fuel costs and emissions, and find the best compromise value. • We introduce differential evolution operator into quantum particle swarm optimization (QPSO). • We introduce crossover operator into quantum particle swarm optimization (QPSO). • Adaptive control is adopted for crossover probability. Consumption of traditional fossil energy has promoted rapid economic development and caused effects such as climate warming and environmental degradation. In order to solve the problem of environmental economic dispatch (EED), this paper proposes a DE-CQPSO (Differential Evolution-Crossover Quantum Particle Swarm Optimization) algorithm based on the fast convergence of differential evolution algorithms and the particle diversity of crossover operators of genetic algorithms. In order to obtain better optimization results, a parameter adaptive control method is used to update the crossover probability. And the problem of multi-objective optimization is solved by introducing a penalty factor. The experimental results show that: the evaluation index and convergence speed of the DE-CQPSO algorithm are better than QPSO (Quantum Particle Swarm Optimization) and other algorithms, whether it is single-objective optimization of fuel cost and emissions or multi-objective optimization considering both optimization objectives. A good compromise value is verified, which verifies the effectiveness and robustness of the DE-CQPSO algorithm in solving environmental economic dispatch problems. The study provides a new research direction for solving environmental economic dispatch problems. At the same time, it provides a reference for the reasonable output of the unit to a certain extent. [ABSTRACT FROM AUTHOR]

As a practical choice to deal with energy security and low-carbon development, the microgrid can effectively promote the consumption of renewable energy. However, the volatility of renewable energy output affects the stable operation of microgrid. In order to ensure the reliability of power supply and improve the economy and environmental protection, this paper studied the short-term economic-environmental (EED) problem of the microgrid. Based on the dispatching model, this paper introduced the differential evolution (DE) into quantum particle swarm optimization (QPSO) and used the improved QPSO to solve problem. Through Friedman test, the performance is compared. The results show that: First, renewable energy should be preferred for generation, micro gas turbine take priority to meet thermal load, fuel cell, and storage battery are used for power supplement and power transaction. This plan can optimize the units output and reduce the emission of pollution gas on the premise of satisfying the regular operation of the microgrid. Second, in the later stage of improved QPSO, the ability to jump out of local optimal solution is stronger. Then, the improved QPSO can obtain better results. Therefore, the improved QPSO has better performance, and it is more suitable for solving microgrid EED problems than QPSO and CLQPSO. • This paper improves QPSO position update equation based on DE. • A winter dispatch plan of a microgrid is obtained. • Performance comparison of multi-stage algorithm is studied. [ABSTRACT FROM AUTHOR]

The urbanization process and the continuous upgrading of consumption structure have driven the rapid growth of China's residential electricity consumption, making it urgent to strengthen energy conservation and emission reduction in the residential sector. Improving the efficiency of electricity use is an effective method to reduce the consumption of electricity, but the rebound effect (RE) also emerges. Is it still conducive to saving electricity? In response to this question, this article selects the relevant data in China during 2010–2016 to construct the panel linear model and the panel threshold model respectively to analyze the direct RE of residential electricity consumption. The results show that: (1) The average RE of China's residential electricity use is 84.94%. It indicates that energy efficiency improvement can lower residents' electricity use, but only 15.06% of the expected target can be achieved. (2) The direct RE in high-income regime (PGDP>76023.67) and low-income regime (PGDP≤76023.67) is 59.15% and 80.79% respectively, meaning that energy efficiency measures in the high-income regime are more effective. (3) The direct RE in the high-population regime (POP>6083.28) and low-population regime (POP≤6083.68) is 120.09% and 83.91% respectively, indicating that energy efficiency improvement in the high-population regime has intensified residents' electricity consumption. Therefore, to maximum energy saving effect, the government should take the inter-provincial heterogeneity of the RE into consideration and introduce market-oriented measures such as price and tax to restrain it. Image 1 • The direct rebound effect of China's residential electricity use is 84.94%. • The direct rebound effect is 59.15% (80.79%%) in the high (low) income regime. • The direct rebound effect is 120.09% (83.91%) in the high (low) population regime. • The population has the greatest impact on residential electricity use, followed by PGDP. [ABSTRACT FROM AUTHOR]

Due to its characteristics of nearby power generation, grid-connection, conversion and use, rooftop photovoltaic power generation has formed the advantages of less investment, flexible, efficient and environmental protection, with broad prospects for development. Therefore, studying its economic performance is of great significance to investment decision and policy improvement. Under the current technical cost and policy conditions of rooftop photovoltaic in China, this paper constructs a cost-benefit analysis model considering the impact of inflation on cash flow. The results show that: For small rooftop photovoltaic in China, first of all, under the existing subsidy price and cost, its investment payback period is short and the risk is low. Secondly, the average internal rate of return is more than 10%, and the levelized cost of electricity is 0.2727–0.5573CNY/kWh, so the economic performance is good. Then, although the subsidy price has been lowered twice in a row in 2018, its economic performance is still relatively good. Finally, in the economic performance analysis of rooftop photovoltaic, besides the influence of power generation capacity, loan interest rate, construction cost and other factors, the time value of capital and inflation are also factors that cannot be ignored. • The analysis is based on current policy and technology levels. • The object of analysis is industrial and commercial household photovoltaic. • The inflation rate is added to the formula for calculating various economic indicators. [ABSTRACT FROM AUTHOR]